As the information society becomes increasingly flooded with digital images, the need for efficient image retrieval systems increases as well. To handle the vast amounts of data involved, the indexing process needs to be run automatically, using content-based descriptors extracted directly from the digital image, such as colour composition, shape and texture features. These content-based image retrieval systems are often slow and cumbersome, and can appear confusing to an ordinary user who does not understand the underlying mechanisms. One step towards more efficient and user-friendly retrieval systems might be to adjust the weight placed on various descriptors depending on which image category is being searched for. The results of this thesis show that certain categories of digital images would benefit from having extra weight assigned to colour, texture or shape features when searching for images of that category.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hb-19515 |
| Date | January 2009 |
| Creators | Larsson, Carl |
| Publisher | Högskolan i Borås, Institutionen Biblioteks- och informationsvetenskap / Bibliotekshögskolan, University of Borås/Swedish School of Library and Information Science (SSLIS) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | Swedish |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | Magisteruppsats i biblioteks- och informationsvetenskap vid institutionen Biblioteks- och informationsvetenskap, 1654-0247 ; 2009:49 |
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